博碩士論文 103428014 完整後設資料紀錄

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DC.contributor財務金融學系zh_TW
DC.creator洪禎蔚zh_TW
DC.creatorZhen-Wei Hongen_US
dc.date.accessioned2016-7-5T07:39:07Z
dc.date.available2016-7-5T07:39:07Z
dc.date.issued2016
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=103428014
dc.contributor.department財務金融學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本論文研究演算法交易(algorithmic trading)對外匯市場價格效率性的影響,採用歐元兌美元及日圓兌美元的日內交易報價資料,建構結構性向量自我迴歸(SVAR)模型進行分析,發現演算法交易與市場交易規模呈現相反的趨勢線圖,且演算法交易與市場價格效率性呈現反向關係,即演算法交易傾向在市場效率性較差時進入市場,最後,發現當演算法交易愈活絡時,市場效率性會隨之提升,說明演算法交易能夠改善市場效率,且可進一步推測演算法交易者為資訊交易者(informed traders)。zh_TW
dc.description.abstractThis thesis studies the impact of algorithmic trading (AT) on informational efficiency in the foreign exchange market. My data rely on a novel of intraday data consisting of both quote data and transaction data in two currency pairs: euro-dollar, and dollar-yen. The thesis estimates a structural vector autoregression model. The results show that AT exhibits a strong reverse pattern with trade size, and that greater AT activity is related to lower market efficiency which suggests that algorithmic traders strategically enter the market when informational efficiency is lower. AT is associated with an increase in market efficiency in the subsequent intraday period. The results strongly suggest that algorithmic trading is helpful for market efficiency and algorithmic traders are informed.en_US
DC.subject演算法交易zh_TW
DC.subject外匯市場zh_TW
DC.subject市場價格效率性zh_TW
DC.subject日內資料zh_TW
DC.subjectalgorithmic tradingen_US
DC.subjectforeign exchange marketen_US
DC.subjectmarket efficiencyen_US
DC.subjectintraday dataen_US
DC.title演算法交易對市場日內價格效率性的影響: 以外匯市場為例zh_TW
dc.language.isozh-TWzh-TW
DC.titleThe Effect of Algorithmic Trading on Intraday Price Efficiency: Evidence from Foreign Exchange Marketen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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